sequenzy/skills · Archived

emailcampaignskill

Use when Codex, Hermes, OpenClaw, Claude Code, Cowork, or another AI agent needs to plan, review, implement, audit, or improve email work focused on campaign briefs, audience logic, creative QA, launch readiness, and post-send analysis.

First seen Jul 23, 2026

Installation

$ npx skills add sequenzy/skills --skill emailcampaignskill

Summary

  • Use when Codex, Hermes, OpenClaw, Claude Code, Cowork, or another AI agent needs to plan, review, implement, audit, or improve email work focused on campaign briefs, audience logic, creative QA, launch readiness, and post-send analysis.
  • Triggers include requests about campaign briefs, creative review, performance retrospectives, audience QA, launch checklists, and campaign optimization.

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More details

Agent compatibility

Declared targets from SKILL.md / docs. Unmarked agents are not listed — the skill may still install via the CLI.

Claude Code Declared
Cursor Not declared
Codex Declared
GitHub Copilot Not declared
Windsurf Not declared
Gemini CLI Not declared
Cline Not declared
OpenCode Not declared

Repository health

Stars 2
License LICENSE
Default branch main
Open issues 0
Status Archived

Skill metadata

Parsed from SKILL.md frontmatter.

Declared agents claude-code codex

Package contents

Files included with this skill beyond the listing page.

  • skill md SKILL.md 3,452 B
  • docs SUMMARY.md 415 B

History

  1. First seen on skills.sh
  2. First recorded snapshot · 2 installs

SKILL.md

Email Campaign Skill

Run the campaign as a controlled operation: brief, audience, creative, QA, launch, monitor, learn.

Decision Lens

  • Primary lens: campaign briefs, audience logic, creative QA, launch readiness, and post-send analysis.
  • Common request signals: campaign briefs, creative review, performance retrospectives, audience QA, launch checklists, and campaign optimization.
  • Default posture: Run the campaign as a controlled operation: brief, audience, creative, QA, launch, monitor, learn.
  • Useful output family: campaign briefs, audience QA tables, creative reviews, launch checklists, test plans, and post-send retrospectives.
  • Production boundary: separate recommendation from execution.
  • Evidence boundary: say which source material supports the recommendation.
  • Review boundary: identify the human owner for risky changes.
  • Data boundary: do not assume missing fields, consent, or suppression state.
  • Platform boundary: describe provider-specific steps in operational language.
  • Measurement boundary: define what success or recovery will look like.
  • Handoff boundary: make the next step clear to another agent.
  • Rollback boundary: name the safest way to undo live-system changes.
  • Escalation boundary: stop when legal, compliance, DNS, or sending authority is unclear.

When To Use

Use this skill for campaign briefs, audience logic, creative QA, launch readiness, and post-send analysis. It is designed for agent workflows where email work must be specific, reviewable, and safe across planning, drafting, implementation, QA, or operational handoff.

Operating Workflow

  1. Start with the campaign brief: objective, audience, offer, send window, success metric, constraints, and approval owner.
  2. Validate audience logic before copy, including inclusions, exclusions, consent, suppression, and expected recipient count.
  3. Review creative for promise match across subject, preview, body, proof, CTA, landing page, and follow-up path.
  4. Prepare launch QA: links, tracking, personalization, rendering, plain-text fallback, footer, and reply handling.
  5. For analysis, compare performance against baseline, segment, source, and hypothesis rather than judging one metric alone.
  6. Return a launch decision or retrospective with next actions and risks.

Review Criteria

  • The campaign has one primary goal and one primary CTA.
  • Audience eligibility and exclusions are written in operational terms.
  • The creative does not promise more than the landing page delivers.
  • Post-send analysis includes deliverability and list-quality context.
  • Recommendations separate immediate fixes from future tests.

Output Pattern

Return campaign briefs, audience QA tables, creative reviews, launch checklists, test plans, and post-send retrospectives. Keep recommendations concrete. Separate analysis from live-system actions, and require explicit approval before sending email, importing contacts, changing DNS, altering suppression rules, or editing production automations.